问题
I have a file of 40 columns and 600 000 rows. After processing it in pandas dataframe, i would like to save the data frame to csv with different spacing length. There is a sep kwarg in df.to_csv, i tried with regex, but i'm getting error
TypeError: "delimiter" must be an 1-character string.
I want the output with different column spacing, as shown below
A B C D E F G
1 3 5 8 8 9 8
1 3 5 8 8 9 8
1 3 5 8 8 9 8
1 3 5 8 8 9 8
1 3 5 8 8 9 8
Using the below code i'm getting the tab delimited. which are all with same spacing.
df.to_csv("D:\\test.txt", sep = "\t", encoding='utf-8')
A B C D E F G
1 3 5 8 8 9 8
1 3 5 8 8 9 8
1 3 5 8 8 9 8
1 3 5 8 8 9 8
1 3 5 8 8 9 8
I don't want to do looping, It might take lot of time for 600k lines.
回答1:
Thank you for comments, It helped me. Below is the code.
import pandas as pd
#Create DataFrame
df = pd.DataFrame({'A':[0,1,2,3],'B':[0,11,2,333],'C':[0,1,22,3],'D':[00,1,2,33]})
#Convert the Columns to string
df[df.columns]=df[df.columns].astype(str)
#Create the list of column separator width
SepWidth = [5,6,3,8]
#Temp dict
tempdf = {}
#Convert all the column to series
for i, eCol in enumerate(df):
tempdf[i] = pd.Series(df[eCol]).str.pad(width=SepWidth[i])
#Final DataFrame
Fdf = pd.concat(tempdf, axis=1)
#print Fdf
#Export to csv
Fdf.to_csv("D:\\test.txt", sep='\t', index=False, header=False, encoding='utf-8')
output of test.txt
0 0 0 0
1 11 1 1
2 2 22 2
3 333 3 33
UPDATE
Tab delimited ('\t') was included in spacing, while using pandas.to_csv. Behalf of pandas.to_csv i'm using below code to save as txt.
numpy.savttxt(file, df.values, fmt='%s')
来源:https://stackoverflow.com/questions/45983286/pandas-data-frame-to-csv-with-more-separator